A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 8, 22:45 UTC
[Refactor] Remove unused dead code (#33718)
Signed-off-by: yewentao256 <zhyanwentao@126.com>
Wentao Ye committed
Feb 4, 2026 at 00:25 UTC
5e1e0a0fbdf52dd21bfa6bc4dd6e88487a917d23
3 files changed
-77
vllm/collect_env.py
-8
@@ -146,14 +146,6 @@ def run_and_parse_first_match(run_lambda, command, regex):
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return match.group(1)
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-def run_and_return_first_line(run_lambda, command):
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- """Run command using run_lambda and returns first line if output is not empty."""
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- rc, out, _ = run_lambda(command)
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- if rc != 0:
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- return None
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- return out.split("\n")[0]
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-
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-
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def get_conda_packages(run_lambda, patterns=None):
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if patterns is None:
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patterns = DEFAULT_CONDA_PATTERNS
vllm/compilation/fx_utils.py
-15
@@ -18,21 +18,6 @@ def is_auto_func(node: fx.Node, op: OpOverload) -> bool:
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return is_func(node, auto_functionalized) and node.args[0] == op
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-# Returns the first specified node with the given op (if it exists)
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-def find_specified_fn_maybe(nodes: Iterable[fx.Node], op: OpOverload) -> fx.Node | None:
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- for node in nodes:
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- if node.target == op:
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- return node
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- return None
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-
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-
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-# Returns the first specified node with the given op
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-def find_specified_fn(nodes: Iterable[fx.Node], op: OpOverload) -> fx.Node:
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- node = find_specified_fn_maybe(nodes, op)
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- assert node is not None, f"Could not find {op} in nodes {nodes}"
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- return node
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-
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-
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# Returns the first auto_functionalized node with the given op (if it exists)
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def find_auto_fn_maybe(nodes: Iterable[fx.Node], op: OpOverload) -> fx.Node | None:
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for node in nodes:
vllm/config/utils.py
-54
@@ -14,7 +14,6 @@ from dataclasses import MISSING, Field, field, fields, is_dataclass
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from itertools import pairwise
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from typing import TYPE_CHECKING, Any, Protocol, TypeVar, cast
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-import regex as re
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import torch
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from pydantic import ConfigDict
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from pydantic.dataclasses import dataclass
@@ -144,34 +143,6 @@ def getattr_iter(
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return default_factory() if default_factory is not None else default
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-def contains_object_print(text: str) -> bool:
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- """
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- Check if the text looks like a printed Python object, e.g.
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- contains any substring matching the pattern: "at 0xFFFFFFF>"
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- We match against 0x followed by 2-16 hex chars (there's
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- a max of 16 on a 64-bit system).
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-
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- Args:
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- text (str): The text to check
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-
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- Returns:
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- result (bool): `True` if a match is found, `False` otherwise.
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- """
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- pattern = r"at 0x[a-fA-F0-9]{2,16}>"
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- match = re.search(pattern, text)
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- return match is not None
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-
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-
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-def assert_hashable(text: str) -> bool:
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- if not contains_object_print(text):
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- return True
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- raise AssertionError(
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- f"vLLM tried to hash some configs that may have Python objects ids "
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- f"in them. This is a bug, please file an issue. "
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- f"Text being hashed: {text}"
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- )
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-
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-
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def get_attr_docs(cls: type[Any]) -> dict[str, str]:
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"""
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Get any docstrings placed after attribute assignments in a class body.
@@ -354,31 +325,6 @@ def hash_factors(items: dict[str, object]) -> str:
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return hashlib.sha256(json.dumps(items, sort_keys=True).encode()).hexdigest()
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-def handle_deprecated(
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- config: ConfigT,
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- old_name: str,
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- new_name_or_names: str | list[str],
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- removal_version: str,
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-) -> None:
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- old_val = getattr(config, old_name)
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- if old_val is None:
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- return
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-
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- if isinstance(new_name_or_names, str):
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- new_names = [new_name_or_names]
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- else:
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- new_names = new_name_or_names
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-
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- msg = (
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- f"{old_name} is deprecated and will be removed in {removal_version}. "
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- f"Use {', '.join(new_names)} instead."
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- )
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- logger.warning(msg)
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-
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- for new_name in new_names:
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- setattr(config, new_name, old_val)
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-
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-
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@dataclass
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class Range:
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"""